code: def find_step_scaler_on_rect_grid(grid, center, std=1):
      """
      Function returns multivariate gaussian around the center
      with specified standard deviation.
  
      Parameters
      ----------
      {find_neighbour_distance.grid}
  
      {find_neighbour_distance.center}
  
      std : int, float
          Gaussian standard deviation. Defaults to ``1``.
      """
      distances = find_neighbour_distance(grid, center)
      gaussian_array = sum(
          gaussian_df(dist, std=std) for dist in distances
      )
      return gaussian_array / grid.ndim
  
file_path: neupy/neupy/algorithms/competitive/neighbours.py
imports: from __future__ import division
  import numpy
  from neupy.core.docs import shared_docs
label_desc: Use image node_id 3 for calling a global function with example usage: find_step_scaler_on_rect_grid(grid, center, std) and returns: unknown